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A CAUSALITY ANALYSIS OF SOCIETAL RISK PERCEPTION AND STOCK MARKET VOLATILITY IN CHINA 被引量:3

A CAUSALITY ANALYSIS OF SOCIETAL RISK PERCEPTION AND STOCK MARKET VOLATILITY IN CHINA
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摘要 Modem China is undergoing a variety of social conflicts as the arrival of new era with thetransformation of the principal contradiction. Then monitoring the society stable is a huge workload.Online societal risk perception is acquired by mapping on-line public concerns respectively intosocietal risk events including national security, economy & finance, public morals, daily life, socialstability, government management, and resources & environment, and then provides one kind ofmeasurement toward the society state. Obviously, stable and harmonious social situations are the basicguarantee for the healthy development of the stock market. Thus we concern whether the variations ofthe societal risk are related to stock market volatility. We study their relationships by two steps, firstthe relationships between search trends and societal risk perception; next the relationships betweensocietal risk perception and stock volatility. The weekend and holiday effects in China stock market aretaken into consideration. Three different econometric methods are explored to observe the impacts ofvariations of societal risk on Shanghai Composite Index and Shenzhen Composite Index. 3 majorfindings are addressed. Firstly, there exist causal relations between Baidu Index and societal riskperception. Secondly, the perception of finance & economy, social stability, and governmentmanagement has distinguishing effects on the volatility of both Shanghai Composite Index and Shenzhen Composite Index. Thirdly, the weekend and holiday effects of societal risk perception on the stock market are verified. The research demonstrates that capturing societal risk based on on-line public concerns is feasible and meaningful. Modem China is undergoing a variety of social conflicts as the arrival of new era with thetransformation of the principal contradiction. Then monitoring the society stable is a huge workload.Online societal risk perception is acquired by mapping on-line public concerns respectively intosocietal risk events including national security, economy & finance, public morals, daily life, socialstability, government management, and resources & environment, and then provides one kind ofmeasurement toward the society state. Obviously, stable and harmonious social situations are the basicguarantee for the healthy development of the stock market. Thus we concern whether the variations ofthe societal risk are related to stock market volatility. We study their relationships by two steps, firstthe relationships between search trends and societal risk perception; next the relationships betweensocietal risk perception and stock volatility. The weekend and holiday effects in China stock market aretaken into consideration. Three different econometric methods are explored to observe the impacts ofvariations of societal risk on Shanghai Composite Index and Shenzhen Composite Index. 3 majorfindings are addressed. Firstly, there exist causal relations between Baidu Index and societal riskperception. Secondly, the perception of finance & economy, social stability, and governmentmanagement has distinguishing effects on the volatility of both Shanghai Composite Index and Shenzhen Composite Index. Thirdly, the weekend and holiday effects of societal risk perception on the stock market are verified. The research demonstrates that capturing societal risk based on on-line public concerns is feasible and meaningful.
出处 《Journal of Systems Science and Systems Engineering》 SCIE EI CSCD 2018年第5期613-631,共19页 系统科学与系统工程学报(英文版)
基金 This research is supported by National Key Research and Development Program of China (2016YFB1000902) and National Natural Science Foundation of China (61473284 & 71731002).
关键词 Societal risk perception stock market volatility Baidu Index Granger causality test multiple linear regressions Societal risk perception stock market volatility Baidu Index Granger causality test multiple linear regressions
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